Knowledge has the potential to improve healthcare, the health of individuals, and the health of populations. Every decision affecting health should be informed by the best available knowledge. For moral and ethical reasons, it is imperative that each and every member of society have access to what is known at the time they are making health-related choices and decisions.
It is no longer sufficient to represent knowledge in the form of printed words and static pictures. The increasingly rapid rate of scientific discovery necessitates knowledge representations that are more agile and amenable to scalability and mass action. This in turn can enable the continuous cycles of discovery and improvement envisioned as Learning Health Systems. Contemporary digital technology enables knowledge to be represented in computable forms expressed in machine-executable code. Computable knowledge unleashes the potential of information technology to generate and deliver useful information – particularly decision-specific advice – to individuals and organizations with great speed on a worldwide scale. It is essential to take full advantage of these capabilities, while continuing established practices that validate knowledge, preserve it, and ensure that it can be trusted.
There is work to do to mobilize best available health knowledge for the greater good. To begin, biomedical knowledge in computable form must be made interoperable using open standards, and widely available so that it can be used to immediately impact health.
It is time for action on a global scale.
Computable biomedical knowledge (CBK) is the result of an analytic and/or deliberative process about human health, or affecting human health, that is explicit, and therefore can be represented and reasoned upon using logic, formal standards, and mathematical approaches.
We are dedicated to:
Mobilizing biomedical knowledge that can support action toward improving human health. This should be done using computable formats that can be shared and integrated into health information systems and applications.
Efficiently and equitably serving the learning and knowledge needs of all participants, as well as the public good. This will work to significantly reduce health disparities.
Ensuring that the knowledge properly reflects the best and most current evidence and science. This will ensure that knowledge can be trusted for use to improve health and healthcare.
Achieving this through evolution of an open computable biomedical knowledge ecosystem dedicated to achieving the FAIR principles: making CBK easily findable, universally accessible, highly interoperable, and readily reusable.* The current interest in making data FAIR should be matched by equally intense interest in making knowledge FAIR.
We believe that all of the following are important: